Ethanol drinking is a complex trait, and thus influenced by multiple genetic and environmental factors. Examining the influence of one gene at a time ignores the importance of possible interactions (e.g., epistasis, intra-allelic overdominance;see Phillips &Belknap, 2002). We propose to utilize a filial cross approach for the mapping of gene sets that result in excessive alcohol intake. C57BL/6J (B6) x FVB/NJ (FVB) F1 mice have been found to consume more ethanol than even the high ethanol preference B6 strain (Blednov et al., 2005). We will take advantage of this finding to resolve mode of inheritance for excessive drinking by combining quantitative trait locus (QTL) mapping with microarray gene expression analysis to identify colocalization of behavioral (bQTL) and expression QTL (eQTL). In Specific Aim 1, bQTL for excessive voluntary ethanol consumption will be mapped using the B6FVBF2. The F2 will be used to determine the mode of inheritance (additive, fully dominant, overdominant, epistatic) for each QTL taken singly and also in pairwise combinations. In Specific Aim 2, F3-F4 individuals will be used for brain region specific gene expression analyses. Individuals predicted by their genotype to be high or low drinking individuals will be selected for microarray profiling. These data will be subjected to eQTL analyses. This will allow us to identify bQTL and eQTL that are mapped to common chromosomal regions providing evidence of the specific gene(s) influencing the drinking trait. Brain regions to be studied will be selected from target tissues identified by the INIA Neurocircuitry group. In Specific Aim 3, possible genetically correlated responses will be measured to explore putative genetic relationships between the extreme drinking trait and others such as ethanol withdrawal, conditioned taste aversion, withdrawal induced drinking, drinking in the dark, ethanol acceptance, and ethanol conditioned place preference. As we obtain evidence for the specific locations of genes that influence the high drinking trait, other traits will be chosen for examination based on previous QTL mapping data that have identified associations of those traits with the locations we identify. Future work will also be focused on the most significant candidate genes implicated by our combined bQTL:eQTL analyses.